Foundation for the Advancement of Economics and Friedrich Ebert Stiftung (Belgrade) lecture series...

Foundation for the Advancement of Economics andFoundation for the Advancement of Economics and Friedrich Ebert Stiftung (Belgrade) lecture series Friedrich Ebert Stiftung (Belgrade) lecture series

The impact of European The impact of European FDI FDI in the EU 'neighbourhood': in the EU 'neighbourhood':

relative size, geographical scale and relative size, geographical scale and spatial selectivityspatial selectivity

Vassilis Monastiriotis (with Mireia Borrell)Vassilis Monastiriotis (with Mireia Borrell) LSEE – LSE Research on South Eastern Europe European Institute, London School of Economics (Contact: [email protected])

Faculty of Economics, University of Belgrade, 10 September 2013

mailto:[email protected]

IntroductionIntroduction

General motivation / context

EU “approximation” a ‘policy distortion’ Preferential trade, trade re-orientation, institutional convergence

But is the “EU influence” good?

Often, these advantages are assumed (‘given’), even in the context of ‘conditionality without accession’ (!)

Here, we examine one only aspect of the ‘economic’: FDI spillovers One aspect but not a side-issue: impacts on domestic productivity

and thus on industrial structure and international competitiveness Because of FDI’s contribution to political transition (Grabbe, 2006; Bevan/Estrin, 2004) Because of its contribution to economic development (Markusen/Venables,1999)

Why should we care? Iff the ‘EU influence’ is not unidirectional, then there is a role

(and responsibility) for the EU to correct and/or compensate

Institutional(capacities)

Political(democratisation)

Economic(modernisation/growth)


FDI in ENP (vs in CEE)

In CEE, prospect of accession paramount in mobilising foreign investments

Part of changing geographical organisation of production (spatial DoL)

Part of a wider process of restructuring for the European industry

Deeper integration process, stronger / more organic linkages => stronger technology transfers to domestic firms

In ENP (and SEE?) less FDI and with different motives

Less integration, more market capture & resource ‘expropriation’

Still, pref’l framework a motive for more organic / less speculative FDI


Research questions Does EU FDI have positive productivity spillovers?

To justify the FDI attraction policies Does EU FDI have a spillover advantage over FDI of other origins?

To justify the ‘approximation’ policies Does (EU) FDI have different impacts in ENP than in CEE?

Would suggest need to combine openness w/ deeper/political integration… Does (EU) FDI create spatial distortions despite its overall +ve effects?

Would necessitate corrective policy interventions

Empirical analysis Firm-level data (10k+) from BEEPS (28 countries, 2002-2009) Production-function approach to estimate direct and intra-industry

productivity spillovers, looking in particular at:

How these vary across country groups How they vary by origin The geographical scale of spillovers (nat’l/sectoral v reg’l/localised) The spatial selectivity of spillovers (capitals v the rest)


Structure

Introduction

Considerations for the analysisEmpirics – theoretical considerations – data & model

Empirical analysis I: impact of FDI by origin and recipient groupEuropean vs non-European spillovers in ENP, SEE & CEE

Empirical analysis II: scale and location of FDI impactsExamining localisation of spillovers and capital-city effects

Conclusions and policy discussion

Considerations for the analysisConsiderations for the analysis

What we know (empirics) Vertical / inter-industry spillovers / stronger / more positive

Damijan et al, 2003; Gorodnichenko et al, 2007; Nicolini/Resmini, 2010 Horizontal often non-significant or negative (also in LDCs)

Konings, 2001; Javorcik, 2004; Sabirianova et al, 2005 Horizontal (and vertical) conditional / contextual

Firm/sector characteristics (firm size – Pojar, 2012; absorptive capacity / technological

distance – Halpern/Murakozy, 2007; sector/region – Monastiriotis/Jordaan, 2010)

Recipient country characteristics (level of development, corruption, political regime –

Tytell/Yodaeva, 2005) Characteristics related to the foreign investors

(origin, extent of ownership, export-orientation – Javorcik/Spatareanou, 2011)

Significant selection (Jordaan, 2013) & hysterisis (Monastiriotis/Alegria, 2011)Damijan et al, 2013: an

extensive study of effects and conditioning factors

Here, interest is in the geography of spillovers, within a context of political-institutional-economic approximation


On origin and geography

OriginExisting research: different processes and conceptions of ‘proximity’

J&S: distance => local sourcing => vertical spillovers M&A: cultural-technological proximity => more ‘embeddedness’,

greater scope for / more absorbable spillovers (vertical – horizontal)Here: political-inst’l proximity (‘approximation’); more productive due to:

FDI part of ‘strategy’ to strengthen local capacities/markets local links/synergies Local firms more keen to ‘engage’/compete with EU investors more ‘learning’ Institutional approximation (transposition) facilitating/forging such links

larger / more absorbable spillovers

Scale and spaceFDI literature not particularly ‘theoretical’ on this – nor too ‘empirical’ either

Focus on sectors and the nature of spillovers (eg, pecuniary – technological)‘Spatial’ theory directly from ‘economics of agglomeration’ literature

Knowledge spillovers are localised; MAR & Jacobs externalities / economiesSome work on impact of agglomeration (‘local capacities’ / absorption)

Driffield/Hughes, 2003; Haskel et al, 2007; Girma/Wakelin, 2009 (UK); Mullen/Williams, 2007 (USA); Sgard, 2001 (HU); Jordaan, 2008 (MEX); Monastiriotis/Jordaan, 2010 (GR)


Data

Business Environment and Enterprise Performance Survey (BEEPS) EBRD/World Bank survey on firms / business environment Unbalanced panel from three waves – 2002, 2005 and 2009 Survey contains 28k obs (22k/10k after cleaning); 28 transition countries Sample sizes b/w 82 (MG) and 1,000+ (BG, UK, RU, TK, PL, RO, CR) Info on sales, employment, fixed assets, share & nationality of foreign

ownership, share of exports, sector (2-digit NACE), region, etc (info on foreign presence/nationality in cases projected from x-sectional survey)

Independent variable – Foreign share within sector (horizontal) Based on firm-level foreign shares: share of output attributable to

foreign ownership (within sector-year or sector-region-year) Output-based measure, favoured over E-based due to pvity diffs Using 10% threshold for decision not to include to group of

domestic firms – other thresholds (min, maj, full) similar results

Descriptive statistics (next slide)


Table 2. Sample sizes by country (group) and year


Table 3. Foreign ownership shares by country (group) and year


Table 4. FDI inflows as share of GDP (UNDP data)


Method

Production-function approach – total factor productivity effects Sales (Y) a function of labour (E) and capital (FA) Policy variable (spillovers): share of foreign presence (sector/region) Controls (selection etc): sector and country dummies; firm FEs

Estimating model

where y is output (sales) of firm i in sector s of country c in year t; k is capital (fixed assets); l is employment; h is our measure of horizontal FDI; Dc and Dt are vectors of binary dummies for countries and years; e is a normally distributed error; and the b’s are parameters to be estimated

Estimation considerations Clustered standard errors, OLS and FE (within) estimations FEs reduce sample and heterogeneity: only indicatively here No correction for selectivity of capital – little sectoral differences

Aggregate effects

Empirical resultsEmpirical results

Dependent: log(sales) (1) (2) (3) (4) (5) (6) Employment (log) 0.544*** 0.333*** 0.831*** 0.853*** 0.566*** 0.329*** (0.023) (0.056) (0.013) (0.013) (0.023) (0.061) Fixed assets (log) 0.503*** 0.635*** 0.189*** 0.182*** 0.508*** 0.625*** (0.017) (0.017) (0.019) (0.018) (0.021) (0.019) Foreign share (own) 0.198*** 0.181

(0.047) (0.284) Foreign share (sector) -0.0085 -0.213 -0.206** -0.126** 0.694* 2.328*** (0.088) (0.201) (0.074) (0.056) (0.385) (0.659) Foreign share squared (sector)

-0.955* -3.631*** (0.461) (0.884)

Constant 9.813*** 5.248*** 21.06*** 20.87*** 9.171*** 4.774*** (0.435) (0.307) (0.642) (0.569) (0.416) (0.412) Fixed effects

Country, Year

Firm, Year

Country (x) Year

Country (x) Year, Sector

Country, Year,

Sector

Firm, Year,

Sector Observations 10,696 10,696 9,313 9,313 9,313 9,313 R-squared 0.868 0.598 0.922 0.929 0.872 0.634

Direct (own) effect strong and positiveBut not when controlling for selectionEither way, external (horizontal) effect negative and non-significantBut significant with interactive country-year FEs (national trends / country-specific temporal effects)Effect smaller with sector-FEs, suggesting, if anything, selection into low-productivity sectors

But significant non-linearity (also with firm-FEs) hump-shaped effect, positive for low FDI concentrations, negative for high ones

Non-linearity

Empirical resultsEmpirical resultsPredicted total effects on firm productivity (vertical axis) for different values of sectoral shares of foreign presence (horizontal axis) based on alternative estimation equations

Col. 5

Col. 6

Stock-taking – aggregate analysis

Overall, in our sample countries, foreign investments offer little benefits to the sectors in which they locate (in terms of spillovers)

There is a direct positive effect for the firms that receive the foreign investment – although, still, this may be subject to self-selection

Some evidence of positive spillovers in sectors where foreign presence is (positive but) at rather low levels – although country differences in temporal dynamics may exaggerate this effect

Firms in sectors that are dominated by foreign-owned production (well above 50%) show in fact lower productivity

When restricting the sample to surviving domestic firms only(FE estimation) the effect becomes more negative

This suggests that this effect is not compositional (e.g., creaming-off via take-overs or crowding-out via exit) but a pure negative externality


Impact of origin / destination

Empirical resultsEmpirical results Hypothesis 1: origin matters / EU advantageHypothesis 2: destination matters

H1 confirmed: EU FDI significantly more advantageousAlthough insignificant with country-specific time effects, difference from non-EU FDI remains (and is significant)

Difference remains also in FE & non-linear specifications (EU FDI has hump-shaped effect, non-EU linear negative) Impact negative insignificant in CEE: benefits exhausted?

But very strongly hump-shaped (essentially always positive) in SEE: lack of domestic capital/technology base?

In ENP the effect highly insignificant: suggesting perhaps a capacity (absorption) issue?

(1) (2) (3) (4) (5) (6) (7) (8)

ALL ALL CEE SEE ENP CEE SEE ENP

Employment 0.566*** 0.853*** 0.793*** 0.397*** 0.607*** 0.793*** 0.384*** 0.609***

(0.009) (0.013) (0.026) (0.045) (0.042) (0.027) (0.044) (0.043) Fixed assets 0.508*** 0.182*** 0.253*** 0.704*** 0.477*** 0.254*** 0.710*** 0.476***

(0.006) (0.018) (0.027) (0.059) (0.029) (0.028) (0.060) (0.030) Horizontal (total)

-0.0461 3.130*** -0.135

(0.599) (1.000) (0.566)

Horizontal squared (total)

-0.0309 -3.437*** 0.0590

(0.689) (1.052) (0.682) EU horizontal 0.362*** 0.0006

-0.0721 1.308** 0.567*

(0.093) (0.047)

(0.131) (0.576) (0.282) Non-EU horizontal

-0.267* -0.295***

-0.335** 1.003 -0.0427

(0.139) (0.094) (0.153) (1.490) (0.331) Constant 9.179*** 20.84*** 8.265*** 5.171*** 8.234*** 8.271*** 5.266*** 8.179*** (0.155) (0.575) (0.313) (1.272) (0.456) (0.309) (1.277) (0.429) Fixed effects Country,

Year, Sector

Country (x) Year, Sector

Country, Year,

Sector

Country, Year,

Sector

Country, Year,

Sector

Country, Year,

Sector

Country, Year,

Sector

Country, Year,

Sector Observations 9,313 9,313 4,233 1,581 3,499 4,233 1,581 3,499 R-squared 0.872 0.929 0.913 0.876 0.867 0.913 0.876 0.867

Hypothesis 3: EU role by destination

In all cases productivity advantage for EU FDI: - significantly positive in the SEE and ENP, where

non-EU is non-significant (but +ve in SEE) - EU negative non-significant in CEE, compares favourably to non-EU (significant negative)

Stock-taking – role of European FDI

Overall, the results offer support to the underlying hypothesis that the origin of FDI matters, not only in itself but also in relation to the recipient country

In the CEECs, where levels of development are comparatively high and where economic openness happened earlier / faster, the benefits

from FDI, in an intra-industry sense, seem to have been exhausted – for both EU and non-EU FDI

Instead, in the SEECs, where the EU has been playing a pivotal role for political-economic stabilisation and development, the productivity

effects of European FDI are exceptionally strong and much more significant than spillovers from FDI of other origins

Finally, in the ENP region, where EU’s involvement is also preferential but much less significant, or influential, European FDI produces smaller spillovers, albeit still more beneficial ones compared to FDI from other regions


Impact of geography / scale

Empirical resultsEmpirical results (1) (2) (3) (4) (5) (6) (7) Employment 0.853*** 0.853*** 0.853*** 0.853*** 0.853*** 0.853*** 0.853*** 0.854***

(0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) Fixed assets 0.182*** 0.182*** 0.182*** 0.182*** 0.182*** 0.182*** 0.182*** 0.182***

(0.018) (0.018) (0.018) (0.018) (0.018) (0.018) (0.018) (0.018) FP (region-sector) 0.0197 0.515***

(0.067) (0.166) FP^2 (region-sector) -0.727***

(0.196) EU FP (region-sector) 0.0962

(0.075) Non-EU FP (region-sector)

-0.157 (0.117)

Interactions Capital regions (x) …

FP (sector) 0.0900 0.813*** (0.121) (0.274)

FP (sector-region) 0.193* 1.002*** (0.102) (0.187)

FP^2 (sector) -1.154*** (0.317)

FP^2 (sector-region) -1.233*** (0.244)

EU FP (region-sector) 0.215** (0.091)

Non-EU FP (region-sector)

-0.097 (0.152)

Other regions (x) … FP (sector) -0.212*** -0.140

(0.061) (0.209) FP (sector-region) -0.098 0.172

(0.073) (0.203) FP^2 (sector) -0.051

(0.260) FP^2 (sector-region) -0.369


(0.094) Non-EU FP (region-

sector) -0.194 (0.136)

Constant 20.82*** 20.77*** 20.81*** 20.88*** 20.86*** 20.87*** 20.83*** 20.84*** (0.583) (0.586) (0.580) (0.564) (0.575) (0.564) (0.579) (0.579)

Observations 9,313 9,313 9,313 9,313 9,313 9,313 9,313 9,313 R-squared 0.929 0.929 0.929 0.929 0.929 0.929 0.929 0.929

Is the absence of strong results due to our focus at the national-sectoral level?

Are spillovers (more) localised?

As before, strong evidence of non-linearity (across specifications): concentration matters (adversely)

But the effect is flatter, suggesting little localisation and probably evidence of spatial heterogeneity

Impact of geography / scale

Counter to expectations, no localised effects either

Effect (at least) positive, but insignificant(also with firm-FEs, non-interactive dummies, etc)

The hump-shaped effect is also consistently flatter for the three country blocks (and only significant in SEE)

But note that the region-wide measure (not region-sector) returns strong positive spillovers

Spillovers are inter-industry (region-wide): urbanisation, not localisation, effects

EU FDI still more beneficial, but effect non-significant: by all evidence, intra-industry (horizontal) spillovers are not localised

But for intra-industry at least, the effects appear to be heterogeneous in space: the negative effect is driven by domestic firms in the periphery

EU FDI still more beneficial, but effect non-significant: by all evidence, intra-industry (horizontal) spillovers are not localised

In the case of the region-specific measure, FDI returns a positive spillover in capital regions

Spillover effect more positive everywhere, suggesting that localisation matters, but rather differently in different types of regions

The picture is similar when we examine non-linearities:

For capital regions, strong hump-shaped spillovers and stronger with co-location (spillovers are localised)

The picture is similar when we examine non-linearities:

For capital regions, strong hump-shaped spillovers and stronger with co-location (spillovers are localised)

For other regions, spillovers are insignificant / negative (although still less so with co-location)

These patterns appear to be strongest in CEE and weakest in SEE (not shown):

Especially in the CEECs, negative spillovers / exhaustion of benefits comes from the peripheral regions

Concerning the origin distinction:

EU FDI more advantageous in both types of regions

FDI of any origin more advantageous in capital regions

EU FDI in capital regions produces clear positive spillovers

(1) (2) (3) (4) (5) (6) (7) Employment 0.853*** 0.853*** 0.853*** 0.853*** 0.853*** 0.853*** 0.853*** 0.854***

(0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) Fixed assets 0.182*** 0.182*** 0.182*** 0.182*** 0.182*** 0.182*** 0.182*** 0.182***

(0.018) (0.018) (0.018) (0.018) (0.018) (0.018) (0.018) (0.018) FP (region-sector) 0.0197 0.515***

(0.067) (0.166) FP^2 (region-sector) -0.727***


(0.075) Non-EU FP (region-sector)

-0.157 (0.117)

Interactions Capital regions (x) …

FP (sector) 0.0900 0.813*** (0.121) (0.274)

FP (sector-region) 0.193* 1.002*** (0.102) (0.187)

FP^2 (sector) -1.154*** (0.317)

FP^2 (sector-region) -1.233*** (0.244)

EU FP (region-sector) 0.215** (0.091)

Non-EU FP (region-sector)

-0.097 (0.152)

Other regions (x) … FP (sector) -0.212*** -0.140

(0.061) (0.209) FP (sector-region) -0.098 0.172

(0.073) (0.203) FP^2 (sector) -0.051

(0.260) FP^2 (sector-region) -0.369


(0.094) Non-EU FP (region-

sector) -0.194 (0.136)

Constant 20.82*** 20.77*** 20.81*** 20.88*** 20.86*** 20.87*** 20.83*** 20.84*** (0.583) (0.586) (0.580) (0.564) (0.575) (0.564) (0.579) (0.579)

Observations 9,313 9,313 9,313 9,313 9,313 9,313 9,313 9,313 R-squared 0.929 0.929 0.929 0.929 0.929 0.929 0.929 0.929

Stock-taking – geography of spillovers

Evidence of localised spillovers particularly weak – e.g., in quadratic model hump-shaped curve much flatter than in sectoral analysis

Region-wide FDI, however, produces strong positive spillovers (vertical / inter-industry spillovers; urbanisation effects)

But these effects are conditional on space / heterogenous: capital regions consistently benefit more / suffer less (esp. in CEE) hump-shaped non-linearity essentially only in capital regionsconditioning on space, localisation effect becomes larger

Implication: even when overall effect is positive (moderate concentration, European origin, etc), foreign presence has a detrimental spatial

effect as it tends to increase productivity differences b/w capital-city regions (which already possess development/agglomeration advantages) and the rest

Effect not due to concentration of FDI in capitals (see result stability in cols.6 & 7)But given this concentration, the spillover advantage observed in capital regions

implies necessarily that foreign-frim presence magnifies regional disparities in the host economies (at least those of our sample)


Summary and conclusionsSummary and conclusions

Starting points Knowledge/empirics of FDI spillovers extensive/consolidated – but little

emphasis on supra- and sub-national geographies and political contexts Here, examined the ‘origin & geography’ issue within context of EU external

relations (neigh/hood policy): inst’l approximation – enhanced econ flows Research questions: Is it good? Is it worth it? Is it cost-free (or distortive)?

Main findings / key highlights (more, in the paper…) EU FDI has ‘productivity advantage’ in ‘neighbourhood’ (more +ve / less –ve)

If EU MNCs not systematically more productive, policy a likely source of advantage FDI spillovers in ENP not maximised (countries not sufficiently ‘developed’?)

More ‘approximation’ can bring benefits as in CEE (past) and SEE (today) Spillovers not too localised but stronger in capital regions

Agglomeration matters; but spatially distortive / enhancing regional disparities Conclusions for policy

Approximation process and ‘gravitational pull’ create an inadvertent reorientation of trade and economic / production structures With it, come costs: productivity spillovers that are often negative; spatial

distortions producing more inequality / geographical differentiation Role for (EU) policy to correct/compensate : existing policies and assistance

instruments to obtain spatial focus; new ones to address spatial imbalances

About LSEE . Research unit at the European Institute, LSE

bringing together LSE’s expertise on SEE, complementing the work of the HO and the

Contemporary Turkish Studies Programme

Aims to provide a platform for high quality, independent research & facilitate research collaborations and public dialogue on SEE, including via academic visits & public events

LSEE has developed an extensive network of research and institutional collaborations with a range of academic, governmental and international bodies, including the EC and the RCC.

LSEE researchers and research affiliates are engaged in a broad range of in-house and externally funded projects in the region, along three broad themes:

Social Cohesion (social policy, regional policy, labour markets)Macroeconomy (European integration, institutional reform, growth)Security/Minorities (international relations, state-building, civil society)

http://www.lse.ac.uk/LSEE

http://www2.lse.ac.uk/europeanInstitute/Research/LSEE/Home.aspx

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